AI & Automation
Intelligent systems that learn, adapt, and create real leverage.
Start a projectAI is only valuable when it solves a real problem. We don't build AI for its own sake — we identify the workflows, decisions, and bottlenecks in your business where intelligence creates measurable leverage, then engineer systems that deliver it reliably. From LLM integrations to custom ML pipelines, we build AI that works in production.
How we deliver it
LLM integration & orchestration
Production-grade integrations with OpenAI, Anthropic, and open-source models. We handle prompt engineering, context management, token optimisation, and fallback strategies.
Retrieval-augmented generation (RAG)
AI that knows your data. We build RAG pipelines that ground LLM responses in your documents, knowledge bases, and databases — reducing hallucinations and increasing accuracy.
Intelligent automation
Workflows that used to require human judgment, automated with AI. Document processing, classification, extraction, routing — built to run at scale without supervision.
AI agents & tool use
Autonomous agents that can browse, search, write, and execute — built with LangChain or custom orchestration frameworks, with guardrails and human-in-the-loop controls.
Anomaly detection & forecasting
Custom ML models for time-series forecasting, anomaly detection, and predictive analytics — trained on your data, deployed to your infrastructure.
Evaluation & observability
AI systems need monitoring too. We build evaluation frameworks, track model performance over time, and alert on quality degradation before users notice.
- AI feature or standalone system
- Prompt engineering and evaluation framework
- Vector database and retrieval pipeline
- Monitoring and cost management setup
- Integration with existing systems
- Documentation and team training
Our process
Use case validation
We audit your workflows to identify where AI creates genuine leverage — not just where it's technically possible.
Prototype & evaluate
A working prototype in 2–3 weeks, evaluated against real data with measurable quality metrics before we commit to a full build.
Pipeline engineering
Production-grade data pipelines, vector stores, and model serving infrastructure built for reliability and cost efficiency.
Integration & testing
Deep integration with your existing systems, with comprehensive testing including adversarial inputs and edge cases.
Monitoring & iteration
Ongoing evaluation of model performance, cost tracking, and iterative improvement as your data and requirements evolve.
Common questions
Related services
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